pacman::p_load(tmap, sf, DT, stplanr, tidyverse)In-class Exercise 11
Import packages
Flow model
Aspatial OD data
odbus <- read_csv("C:/guacodemoleh/IS415-GAA/Hands-on_Ex/Hands-on_Ex11/data/aspatial/origin_destination_bus_202210.csv")odbus$ORIGIN_PT_CODE <- as.factor(odbus$ORIGIN_PT_CODE)
odbus$DESTINATION_PT_CODE <- as.factor(odbus$DESTINATION_PT_CODE) odbus6_9 <- odbus %>%
filter(DAY_TYPE == "WEEKDAY") %>%
filter(TIME_PER_HOUR >= 6 &
TIME_PER_HOUR <= 9) %>%
group_by(ORIGIN_PT_CODE,
DESTINATION_PT_CODE) %>%
summarise(TRIPS = sum(TOTAL_TRIPS))datatable(odbus6_9)write_rds(odbus6_9, "data/rds/odbus6_9.rds")Geospatial Bus Stop Data
busstop <- st_read("C:/guacodemoleh/IS415-GAA/Hands-on_Ex/Hands-on_Ex11/data/geospatial/BusStop.shp")Reading layer `BusStop' from data source
`C:\guacodemoleh\IS415-GAA\Hands-on_Ex\Hands-on_Ex11\data\geospatial\BusStop.shp'
using driver `ESRI Shapefile'
Simple feature collection with 5159 features and 3 fields
Geometry type: POINT
Dimension: XY
Bounding box: xmin: 3970.122 ymin: 26482.1 xmax: 48284.56 ymax: 52983.82
Projected CRS: SVY21Geospatial Singapore Boundary Layer
mpsz <- read_rds("data/rds/mpsz.rds")mpszSimple feature collection with 332 features and 6 fields
Geometry type: MULTIPOLYGON
Dimension: XY
Bounding box: xmin: 2667.538 ymin: 15748.72 xmax: 56396.44 ymax: 50256.33
Projected CRS: SVY21 / Singapore TM
First 10 features:
SUBZONE_N SUBZONE_C PLN_AREA_N PLN_AREA_C REGION_N
1 MARINA EAST MESZ01 MARINA EAST ME CENTRAL REGION
2 INSTITUTION HILL RVSZ05 RIVER VALLEY RV CENTRAL REGION
3 ROBERTSON QUAY SRSZ01 SINGAPORE RIVER SR CENTRAL REGION
4 JURONG ISLAND AND BUKOM WISZ01 WESTERN ISLANDS WI WEST REGION
5 FORT CANNING MUSZ02 MUSEUM MU CENTRAL REGION
6 MARINA EAST (MP) MPSZ05 MARINE PARADE MP CENTRAL REGION
7 SUDONG WISZ03 WESTERN ISLANDS WI WEST REGION
8 SEMAKAU WISZ02 WESTERN ISLANDS WI WEST REGION
9 SOUTHERN GROUP SISZ02 SOUTHERN ISLANDS SI CENTRAL REGION
10 SENTOSA SISZ01 SOUTHERN ISLANDS SI CENTRAL REGION
REGION_C geometry
1 CR MULTIPOLYGON (((33222.98 29...
2 CR MULTIPOLYGON (((28481.45 30...
3 CR MULTIPOLYGON (((28087.34 30...
4 WR MULTIPOLYGON (((14557.7 304...
5 CR MULTIPOLYGON (((29542.53 31...
6 CR MULTIPOLYGON (((35279.55 30...
7 WR MULTIPOLYGON (((15772.59 21...
8 WR MULTIPOLYGON (((19843.41 21...
9 CR MULTIPOLYGON (((30870.53 22...
10 CR MULTIPOLYGON (((26879.04 26...Geospatial data wrangling
busstop <- st_set_crs(busstop,3414)
mpsz <- st_set_crs(mpsz, 3414)
busstop_mpsz <- st_intersection(busstop, mpsz) %>%
select(BUS_STOP_N, SUBZONE_C) %>%
st_drop_geometry()
Note
st_intersection()is used to perform point and polygon and the output will be point sf objectselect()is used to retain the BUS_STOP_N and SUBZONE_C in the busstop_mpsz sf data framefive bus stops are excluded in the resultant data frame since they are outside the Singapore boundary.
datatable(busstop_mpsz)write_rds(busstop_mpsz, "data/rds/busstop_mpsz.rds")Now append the origin subzone code from busstop_mpsz onto odbus6_9 data frame.
od_data <- left_join(odbus6_9 , busstop_mpsz,
by = c("ORIGIN_PT_CODE" = "BUS_STOP_N")) %>%
rename(ORIGIN_BS = ORIGIN_PT_CODE,
ORIGIN_SZ = SUBZONE_C,
DESTIN_BS = DESTINATION_PT_CODE)Check if there are any duplicates
duplicate <- od_data %>%
group_by_all() %>%
filter(n()>1) %>%
ungroup()We can use the unique() function to retain unique records.
od_data <- unique(od_data)Now perform another left join to get form the destination subzones.
od_data <- left_join(od_data , busstop_mpsz,
by = c("DESTIN_BS" = "BUS_STOP_N")) od_data <- od_data %>%
rename(DESTIN_SZ = SUBZONE_C) %>%
drop_na() %>%
group_by(ORIGIN_SZ, DESTIN_SZ) %>%
summarise(MORNING_PEAK = sum(TRIPS))write_rds(od_data, "data/rds/od_data_fii.rds")od_data_fii <- read_rds("data/rds/od_data_fii.rds")Visualising Spatial Interaction
od_data_fij <- od_data[od_data$ORIGIN_SZ!=od_data$DESTIN_SZ,]write_rds(od_data_fij, "data/rds/od_data_fij.rds")od_data_fij <- read_rds("data/rds/od_data_fij.rds")Creating desire lines
flowLine <- od2line(flow = od_data_fij,
zones = mpsz,
zone_code = "SUBZONE_C")write_rds(flowLine, "data/rds/flowLine.rds")flowLine <- read_rds("data/rds/flowLine.rds")Visualise desire lines
Plot a static map with all the flow lines within Singapore.
tm_shape(mpsz) +
tm_polygons() +
flowLine %>%
tm_shape() +
tm_lines(lwd = "MORNING_PEAK",
style = "quantile",
scale = c(0.1, 1, 3, 5, 7, 10),
n = 6,
alpha = 0.3)
It is better to filter for selected flows such that the flow data plotted is less messy.
Restricting the flows to more than or equal to 5000.
tm_shape(mpsz) +
tm_polygons() +
flowLine %>%
filter(MORNING_PEAK >= 5000) %>%
tm_shape() +
tm_lines(lwd = "MORNING_PEAK",
style = "quantile",
scale = c(0.1, 1, 3, 5, 7, 10),
n = 6,
alpha = 0.3)
Calibrating Spatial Interaction Model
Import Packages
pacman::p_load(tmap, sf, sp,
performance, reshape2,
ggpubr, tidyverse, gtsummary)Converting sf data table to SpatialPolygonsDataFrame
mpsz_sp <- as(mpsz, "Spatial")
mpsz_spclass : SpatialPolygonsDataFrame
features : 332
extent : 2667.538, 56396.44, 15748.72, 50256.33 (xmin, xmax, ymin, ymax)
crs : +proj=tmerc +lat_0=1.36666666666667 +lon_0=103.833333333333 +k=1 +x_0=28001.642 +y_0=38744.572 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs
variables : 6
names : SUBZONE_N, SUBZONE_C, PLN_AREA_N, PLN_AREA_C, REGION_N, REGION_C
min values : ADMIRALTY, AMSZ01, ANG MO KIO, AM, CENTRAL REGION, CR
max values : YUNNAN, YSSZ09, YISHUN, YS, WEST REGION, WR Computing distance matrix
dist <- spDists(mpsz_sp,
longlat = FALSE)Label column and row headers
sz_names <- mpsz$SUBZONE_Ccolnames(dist) <- paste0(sz_names)
rownames(dist) <- paste0(sz_names)Pivoting distance values by SUBZONE_C
distPair <- melt(dist) %>%
rename(dist = value)
head(distPair, 10) Var1 Var2 dist
1 MESZ01 MESZ01 0.000
2 RVSZ05 MESZ01 3926.003
3 SRSZ01 MESZ01 3939.108
4 WISZ01 MESZ01 20252.964
5 MUSZ02 MESZ01 2989.984
6 MPSZ05 MESZ01 1431.330
7 WISZ03 MESZ01 19211.836
8 WISZ02 MESZ01 14960.942
9 SISZ02 MESZ01 7515.256
10 SISZ01 MESZ01 6391.342Update intra zone distances
distPair$dist <- ifelse(distPair$dist == 0,
50, distPair$dist)distPair %>%
summary() Var1 Var2 dist
MESZ01 : 332 MESZ01 : 332 Min. : 50
RVSZ05 : 332 RVSZ05 : 332 1st Qu.: 7097
SRSZ01 : 332 SRSZ01 : 332 Median :11864
WISZ01 : 332 WISZ01 : 332 Mean :12193
MUSZ02 : 332 MUSZ02 : 332 3rd Qu.:16388
MPSZ05 : 332 MPSZ05 : 332 Max. :49894
(Other):108232 (Other):108232 Rename the origin and destination fields.
The from locations are denoted by rows, and the to locations are denoted by columns.
distPair <- distPair %>%
rename(orig = Var1,
dest = Var2)write_rds(distPair, "data/rds/distPair.rds")distPair <- read_rds("data/rds/distPair.rds")Preparing flow data
od_data_fii <- read_rds("data/rds/od_data_fii.rds")Compute the total passenger trip between and within planning subzones using the following code chunk.
flow_data <- od_data_fii %>%
group_by(ORIGIN_SZ, DESTIN_SZ) %>%
summarize(TRIPS = sum(MORNING_PEAK)) Separate intra-flow from passenger volume
flow_data$FlowNoIntra <- ifelse(
flow_data$ORIGIN_SZ == flow_data$DESTIN_SZ,
0, flow_data$TRIPS)
flow_data$offset <- ifelse(
flow_data$ORIGIN_SZ == flow_data$DESTIN_SZ,
0.000001, 1)Combine passenger volume data with distance value
flow_data$ORIGIN_SZ <- as.factor(flow_data$ORIGIN_SZ)
flow_data$DESTIN_SZ <- as.factor(flow_data$DESTIN_SZ)Use left_join() to join flow_data and distPair data frame.
flow_data1 <- flow_data %>%
left_join (distPair,
by = c("ORIGIN_SZ" = "orig",
"DESTIN_SZ" = "dest"))Preparing Origin and Destination Attributes
Import population data
pop <- read_csv("C:/guacodemoleh/IS415-GAA/Hands-on_Ex/Hands-on_Ex11/data/aspatial/pop.csv")Geospatial data wrangling
pop <- pop %>%
left_join(mpsz,
by = c("PA" = "PLN_AREA_N",
"SZ" = "SUBZONE_N")) %>%
select(1:6) %>%
rename(SZ_NAME = SZ,
SZ = SUBZONE_C)Preapre origin attribute
flow_data1 <- flow_data1 %>%
left_join(pop,
by = c(ORIGIN_SZ = "SZ")) %>%
rename(ORIGIN_AGE7_12 = AGE7_12,
ORIGIN_AGE13_24 = AGE13_24,
ORIGIN_AGE25_64 = AGE25_64) %>%
select(-c(PA, SZ_NAME))Prepare destination attribute
flow_data1 <- flow_data1 %>%
left_join(pop,
by = c(DESTIN_SZ = "SZ")) %>%
rename(DESTIN_AGE7_12 = AGE7_12,
DESTIN_AGE13_24 = AGE13_24,
DESTIN_AGE25_64 = AGE25_64) %>%
select(-c(PA, SZ_NAME))write_rds(flow_data1, "data/rds/SIM_data.rds")Import model data
SIM_data <- read_rds("data/rds/SIM_data.rds")Check for variables with zero values
summary(SIM_data) ORIGIN_SZ DESTIN_SZ TRIPS FlowNoIntra
Length:14274 Length:14274 Min. : 1.0 Min. : 1.0
Class :character Class :character 1st Qu.: 11.0 1st Qu.: 11.0
Mode :character Mode :character Median : 56.0 Median : 56.0
Mean : 664.3 Mean : 664.3
3rd Qu.: 296.0 3rd Qu.: 296.0
Max. :104167.0 Max. :104167.0
offset dist ORIGIN_AGE7_12 ORIGIN_AGE13_24 ORIGIN_AGE25_64
Min. :1 Min. : 173.8 Min. : 0 Min. : 0 Min. : 0
1st Qu.:1 1st Qu.: 3465.4 1st Qu.: 240 1st Qu.: 460 1st Qu.: 2210
Median :1 Median : 6121.0 Median : 710 Median : 1400 Median : 7030
Mean :1 Mean : 6951.8 Mean :1037 Mean : 2278 Mean :10536
3rd Qu.:1 3rd Qu.: 9725.1 3rd Qu.:1500 3rd Qu.: 3282 3rd Qu.:15830
Max. :1 Max. :26135.8 Max. :6340 Max. :16380 Max. :74610
DESTIN_AGE7_12 DESTIN_AGE13_24 DESTIN_AGE25_64
Min. : 0 Min. : 0 Min. : 0
1st Qu.: 250 1st Qu.: 460 1st Qu.: 2210
Median : 720 Median : 1430 Median : 7120
Mean :1040 Mean : 2305 Mean :10648
3rd Qu.:1500 3rd Qu.: 3290 3rd Qu.:15830
Max. :6340 Max. :16380 Max. :74610 Replace zero values with 0.99.
SIM_data$DESTIN_AGE7_12 <- ifelse(
SIM_data$DESTIN_AGE7_12 == 0,
0.99, SIM_data$DESTIN_AGE7_12)
SIM_data$DESTIN_AGE13_24 <- ifelse(
SIM_data$DESTIN_AGE13_24 == 0,
0.99, SIM_data$DESTIN_AGE13_24)
SIM_data$DESTIN_AGE25_64 <- ifelse(
SIM_data$DESTIN_AGE25_64 == 0,
0.99, SIM_data$DESTIN_AGE25_64)
SIM_data$ORIGIN_AGE7_12 <- ifelse(
SIM_data$ORIGIN_AGE7_12 == 0,
0.99, SIM_data$ORIGIN_AGE7_12)
SIM_data$ORIGIN_AGE13_24 <- ifelse(
SIM_data$ORIGIN_AGE13_24 == 0,
0.99, SIM_data$ORIGIN_AGE13_24)
SIM_data$ORIGIN_AGE25_64 <- ifelse(
SIM_data$ORIGIN_AGE25_64 == 0,
0.99, SIM_data$ORIGIN_AGE25_64)summary(SIM_data) ORIGIN_SZ DESTIN_SZ TRIPS FlowNoIntra
Length:14274 Length:14274 Min. : 1.0 Min. : 1.0
Class :character Class :character 1st Qu.: 11.0 1st Qu.: 11.0
Mode :character Mode :character Median : 56.0 Median : 56.0
Mean : 664.3 Mean : 664.3
3rd Qu.: 296.0 3rd Qu.: 296.0
Max. :104167.0 Max. :104167.0
offset dist ORIGIN_AGE7_12 ORIGIN_AGE13_24
Min. :1 Min. : 173.8 Min. : 0.99 Min. : 0.99
1st Qu.:1 1st Qu.: 3465.4 1st Qu.: 240.00 1st Qu.: 460.00
Median :1 Median : 6121.0 Median : 710.00 Median : 1400.00
Mean :1 Mean : 6951.8 Mean :1036.73 Mean : 2278.59
3rd Qu.:1 3rd Qu.: 9725.1 3rd Qu.:1500.00 3rd Qu.: 3282.50
Max. :1 Max. :26135.8 Max. :6340.00 Max. :16380.00
ORIGIN_AGE25_64 DESTIN_AGE7_12 DESTIN_AGE13_24 DESTIN_AGE25_64
Min. : 0.99 Min. : 0.99 Min. : 0.99 Min. : 0.99
1st Qu.: 2210.00 1st Qu.: 250.00 1st Qu.: 460.00 1st Qu.: 2210.00
Median : 7030.00 Median : 720.00 Median : 1430.00 Median : 7120.00
Mean :10535.93 Mean :1039.98 Mean : 2305.33 Mean :10647.95
3rd Qu.:15830.00 3rd Qu.:1500.00 3rd Qu.: 3290.00 3rd Qu.:15830.00
Max. :74610.00 Max. :6340.00 Max. :16380.00 Max. :74610.00 Unconstrained SIM
uncSIM <- glm(formula = TRIPS ~
log(ORIGIN_AGE25_64) +
log(DESTIN_AGE25_64) +
log(dist),
family = poisson(link = "log"),
data = SIM_data,
na.action = na.exclude)
uncSIM
Call: glm(formula = TRIPS ~ log(ORIGIN_AGE25_64) + log(DESTIN_AGE25_64) +
log(dist), family = poisson(link = "log"), data = SIM_data,
na.action = na.exclude)
Coefficients:
(Intercept) log(ORIGIN_AGE25_64) log(DESTIN_AGE25_64)
17.00287 0.21001 0.01289
log(dist)
-1.51785
Degrees of Freedom: 14273 Total (i.e. Null); 14270 Residual
Null Deviance: 36120000
Residual Deviance: 19960000 AIC: 20040000The output is not very presentable. In view of this, we can use tbl_regression() to present the data.
tbl_regression() is from the gtsummary package
tbl_regression(uncSIM,
intercept=TRUE)| Characteristic | log(IRR)1 | 95% CI1 | p-value |
|---|---|---|---|
| (Intercept) | 17 | 17, 17 | <0.001 |
| log(ORIGIN_AGE25_64) | 0.21 | 0.21, 0.21 | <0.001 |
| log(DESTIN_AGE25_64) | 0.01 | 0.01, 0.01 | <0.001 |
| log(dist) | -1.5 | -1.5, -1.5 | <0.001 |
| 1 IRR = Incidence Rate Ratio, CI = Confidence Interval | |||
To measure how much the model accounts for the variation of trips, we can use R-squared. Let’s create a function for the calculation of it.
CalcRSquared <- function(observed,estimated){
r <- cor(observed,estimated)
R2 <- r^2
R2
}Compute the R-squared of the unconstrained SIM.
CalcRSquared(uncSIM$data$TRIPS, uncSIM$fitted.values)[1] 0.1694734r2_mcfadden(uncSIM)# R2 for Generalized Linear Regression
R2: 0.446
adj. R2: 0.446Origin constrained SIM
orcSIM <- glm(formula = TRIPS ~
ORIGIN_SZ +
log(DESTIN_AGE25_64) +
log(dist),
family = poisson(link = "log"),
data = SIM_data,
na.action = na.exclude)
summary(orcSIM)
Call:
glm(formula = TRIPS ~ ORIGIN_SZ + log(DESTIN_AGE25_64) + log(dist),
family = poisson(link = "log"), data = SIM_data, na.action = na.exclude)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 19.9309957 0.0054015 3689.887 < 2e-16 ***
ORIGIN_SZAMSZ02 0.6805710 0.0052686 129.175 < 2e-16 ***
ORIGIN_SZAMSZ03 0.3597850 0.0054884 65.554 < 2e-16 ***
ORIGIN_SZAMSZ04 -0.1106566 0.0060027 -18.434 < 2e-16 ***
ORIGIN_SZAMSZ05 -0.3140561 0.0067998 -46.186 < 2e-16 ***
ORIGIN_SZAMSZ06 0.0634425 0.0060258 10.528 < 2e-16 ***
ORIGIN_SZAMSZ07 -1.1301580 0.0110298 -102.464 < 2e-16 ***
ORIGIN_SZAMSZ08 -0.6330394 0.0102949 -61.491 < 2e-16 ***
ORIGIN_SZAMSZ09 0.1064915 0.0063450 16.784 < 2e-16 ***
ORIGIN_SZAMSZ10 0.5061899 0.0053889 93.931 < 2e-16 ***
ORIGIN_SZAMSZ11 -1.3167911 0.0144870 -90.895 < 2e-16 ***
ORIGIN_SZAMSZ12 -1.5103004 0.0127453 -118.499 < 2e-16 ***
ORIGIN_SZBDSZ01 1.3626004 0.0051433 264.929 < 2e-16 ***
ORIGIN_SZBDSZ02 0.9554084 0.0059655 160.156 < 2e-16 ***
ORIGIN_SZBDSZ03 1.1476190 0.0054278 211.433 < 2e-16 ***
ORIGIN_SZBDSZ04 2.0110410 0.0046344 433.940 < 2e-16 ***
ORIGIN_SZBDSZ05 1.0658940 0.0053976 197.477 < 2e-16 ***
ORIGIN_SZBDSZ06 1.2719222 0.0054774 232.213 < 2e-16 ***
ORIGIN_SZBDSZ07 -0.5053039 0.0111553 -45.297 < 2e-16 ***
ORIGIN_SZBDSZ08 -0.3556193 0.0102947 -34.544 < 2e-16 ***
ORIGIN_SZBKSZ01 -0.3606399 0.0075473 -47.784 < 2e-16 ***
ORIGIN_SZBKSZ02 0.1357265 0.0061394 22.107 < 2e-16 ***
ORIGIN_SZBKSZ03 0.4101999 0.0058983 69.545 < 2e-16 ***
ORIGIN_SZBKSZ04 -0.3418645 0.0070764 -48.310 < 2e-16 ***
ORIGIN_SZBKSZ05 -0.2986750 0.0074073 -40.322 < 2e-16 ***
ORIGIN_SZBKSZ06 -0.2637855 0.0068739 -38.375 < 2e-16 ***
ORIGIN_SZBKSZ07 0.5498323 0.0051476 106.813 < 2e-16 ***
ORIGIN_SZBKSZ08 -0.0527393 0.0061457 -8.582 < 2e-16 ***
ORIGIN_SZBKSZ09 -0.1564691 0.0067300 -23.249 < 2e-16 ***
ORIGIN_SZBLSZ01 -1.7551329 0.0176599 -99.385 < 2e-16 ***
ORIGIN_SZBLSZ02 -1.9493637 0.0213859 -91.152 < 2e-16 ***
ORIGIN_SZBLSZ03 -2.9057732 0.0535995 -54.213 < 2e-16 ***
ORIGIN_SZBLSZ04 -1.4672066 0.0254726 -57.599 < 2e-16 ***
ORIGIN_SZBMSZ01 0.1806064 0.0060563 29.821 < 2e-16 ***
ORIGIN_SZBMSZ02 -1.4026549 0.0078244 -179.267 < 2e-16 ***
ORIGIN_SZBMSZ03 -0.5976236 0.0063808 -93.660 < 2e-16 ***
ORIGIN_SZBMSZ04 -0.5456513 0.0059061 -92.388 < 2e-16 ***
ORIGIN_SZBMSZ05 -3.1095195 0.0188118 -165.297 < 2e-16 ***
ORIGIN_SZBMSZ06 -3.0273827 0.0194319 -155.794 < 2e-16 ***
ORIGIN_SZBMSZ07 -0.7378197 0.0066865 -110.345 < 2e-16 ***
ORIGIN_SZBMSZ08 -0.9306150 0.0067188 -138.510 < 2e-16 ***
ORIGIN_SZBMSZ09 -1.4137345 0.0101071 -139.876 < 2e-16 ***
ORIGIN_SZBMSZ10 -1.7054195 0.0101582 -167.886 < 2e-16 ***
ORIGIN_SZBMSZ11 -1.2418380 0.0076792 -161.714 < 2e-16 ***
ORIGIN_SZBMSZ12 -1.3746537 0.0109769 -125.231 < 2e-16 ***
ORIGIN_SZBMSZ13 -0.4339494 0.0069335 -62.587 < 2e-16 ***
ORIGIN_SZBMSZ14 -0.9950458 0.0076302 -130.410 < 2e-16 ***
ORIGIN_SZBMSZ15 -0.6544196 0.0068964 -94.892 < 2e-16 ***
ORIGIN_SZBMSZ16 -1.5193747 0.0105329 -144.250 < 2e-16 ***
ORIGIN_SZBMSZ17 -1.6536771 0.0180672 -91.529 < 2e-16 ***
ORIGIN_SZBPSZ01 0.1484355 0.0064734 22.930 < 2e-16 ***
ORIGIN_SZBPSZ02 -0.3602094 0.0073902 -48.741 < 2e-16 ***
ORIGIN_SZBPSZ03 -0.1567975 0.0072226 -21.709 < 2e-16 ***
ORIGIN_SZBPSZ04 0.4504873 0.0058418 77.115 < 2e-16 ***
ORIGIN_SZBPSZ05 0.5028646 0.0053682 93.675 < 2e-16 ***
ORIGIN_SZBPSZ06 -1.0125668 0.0105638 -95.853 < 2e-16 ***
ORIGIN_SZBPSZ07 -0.3859065 0.0098561 -39.154 < 2e-16 ***
ORIGIN_SZBSSZ01 0.1488497 0.0065504 22.724 < 2e-16 ***
ORIGIN_SZBSSZ02 0.4269498 0.0055893 76.387 < 2e-16 ***
ORIGIN_SZBSSZ03 -0.2437385 0.0062020 -39.300 < 2e-16 ***
ORIGIN_SZBTSZ01 0.1987940 0.0066672 29.817 < 2e-16 ***
ORIGIN_SZBTSZ02 -0.4571546 0.0090784 -50.356 < 2e-16 ***
ORIGIN_SZBTSZ03 -0.2697243 0.0077941 -34.606 < 2e-16 ***
ORIGIN_SZBTSZ04 -1.0997236 0.0115225 -95.441 < 2e-16 ***
ORIGIN_SZBTSZ05 -1.0053122 0.0132594 -75.819 < 2e-16 ***
ORIGIN_SZBTSZ06 -1.0841201 0.0102242 -106.035 < 2e-16 ***
ORIGIN_SZBTSZ07 -2.3134497 0.0158499 -145.960 < 2e-16 ***
ORIGIN_SZBTSZ08 -1.1581618 0.0121161 -95.589 < 2e-16 ***
ORIGIN_SZCBSZ01 -1.0805930 0.0577831 -18.701 < 2e-16 ***
ORIGIN_SZCCSZ01 -0.8145372 0.0152638 -53.364 < 2e-16 ***
ORIGIN_SZCHSZ01 0.0377079 0.0133240 2.830 0.004654 **
ORIGIN_SZCHSZ02 -0.6209553 0.0096388 -64.422 < 2e-16 ***
ORIGIN_SZCHSZ03 1.6790244 0.0069559 241.381 < 2e-16 ***
ORIGIN_SZCKSZ01 0.0839586 0.0059934 14.008 < 2e-16 ***
ORIGIN_SZCKSZ02 0.4379511 0.0062289 70.309 < 2e-16 ***
ORIGIN_SZCKSZ03 0.7956950 0.0051892 153.335 < 2e-16 ***
ORIGIN_SZCKSZ04 1.2740323 0.0053165 239.637 < 2e-16 ***
ORIGIN_SZCKSZ05 0.9326213 0.0061807 150.893 < 2e-16 ***
ORIGIN_SZCKSZ06 0.3976273 0.0085639 46.431 < 2e-16 ***
ORIGIN_SZCLSZ01 -0.7522917 0.0094655 -79.477 < 2e-16 ***
ORIGIN_SZCLSZ02 -1.3937450 0.0153260 -90.940 < 2e-16 ***
ORIGIN_SZCLSZ03 -0.7898683 0.0091016 -86.784 < 2e-16 ***
ORIGIN_SZCLSZ04 0.8451512 0.0051258 164.882 < 2e-16 ***
ORIGIN_SZCLSZ05 -1.6573818 0.0166091 -99.788 < 2e-16 ***
ORIGIN_SZCLSZ06 0.9478181 0.0048182 196.716 < 2e-16 ***
ORIGIN_SZCLSZ07 -0.2499753 0.0064632 -38.677 < 2e-16 ***
ORIGIN_SZCLSZ08 0.1350119 0.0069296 19.483 < 2e-16 ***
ORIGIN_SZCLSZ09 -1.3868782 0.0192743 -71.955 < 2e-16 ***
ORIGIN_SZDTSZ02 -3.7535792 0.0871325 -43.079 < 2e-16 ***
ORIGIN_SZDTSZ03 -3.8462041 0.0840156 -45.780 < 2e-16 ***
ORIGIN_SZDTSZ13 -2.9738127 0.0349241 -85.151 < 2e-16 ***
ORIGIN_SZGLSZ01 -1.5175198 0.0110135 -137.787 < 2e-16 ***
ORIGIN_SZGLSZ02 0.2405712 0.0058742 40.954 < 2e-16 ***
ORIGIN_SZGLSZ03 0.1940241 0.0061989 31.300 < 2e-16 ***
ORIGIN_SZGLSZ04 1.0292572 0.0049028 209.931 < 2e-16 ***
ORIGIN_SZGLSZ05 0.9864552 0.0050898 193.811 < 2e-16 ***
ORIGIN_SZHGSZ01 0.3073609 0.0054307 56.597 < 2e-16 ***
ORIGIN_SZHGSZ02 0.3827293 0.0054555 70.154 < 2e-16 ***
ORIGIN_SZHGSZ03 0.2342580 0.0059240 39.544 < 2e-16 ***
ORIGIN_SZHGSZ04 0.8750090 0.0049639 176.275 < 2e-16 ***
ORIGIN_SZHGSZ05 1.1695280 0.0049468 236.420 < 2e-16 ***
ORIGIN_SZHGSZ06 -0.0462411 0.0063805 -7.247 4.25e-13 ***
ORIGIN_SZHGSZ07 0.4488583 0.0055139 81.404 < 2e-16 ***
ORIGIN_SZHGSZ08 0.2236095 0.0061279 36.490 < 2e-16 ***
ORIGIN_SZHGSZ09 -1.6376674 0.0084442 -193.941 < 2e-16 ***
ORIGIN_SZHGSZ10 -2.9849025 0.0501042 -59.574 < 2e-16 ***
ORIGIN_SZJESZ01 0.3926525 0.0056268 69.783 < 2e-16 ***
ORIGIN_SZJESZ02 0.1230160 0.0056864 21.633 < 2e-16 ***
ORIGIN_SZJESZ03 0.0188276 0.0061020 3.085 0.002032 **
ORIGIN_SZJESZ04 -1.3611618 0.0117184 -116.156 < 2e-16 ***
ORIGIN_SZJESZ05 -2.0643662 0.0157083 -131.419 < 2e-16 ***
ORIGIN_SZJESZ06 0.1556368 0.0055245 28.172 < 2e-16 ***
ORIGIN_SZJESZ07 -1.7664532 0.0133171 -132.646 < 2e-16 ***
ORIGIN_SZJESZ08 -0.9115981 0.0138203 -65.961 < 2e-16 ***
ORIGIN_SZJESZ09 0.6121916 0.0060381 101.388 < 2e-16 ***
ORIGIN_SZJESZ10 -1.1953045 0.0233216 -51.253 < 2e-16 ***
ORIGIN_SZJESZ11 -1.4088748 0.0220921 -63.773 < 2e-16 ***
ORIGIN_SZJWSZ01 0.5759093 0.0077741 74.081 < 2e-16 ***
ORIGIN_SZJWSZ02 0.9769314 0.0053029 184.227 < 2e-16 ***
ORIGIN_SZJWSZ03 1.3242695 0.0049068 269.882 < 2e-16 ***
ORIGIN_SZJWSZ04 0.5621088 0.0057831 97.199 < 2e-16 ***
ORIGIN_SZJWSZ05 -1.5744341 0.0146904 -107.174 < 2e-16 ***
ORIGIN_SZJWSZ06 -0.9113320 0.0126913 -71.807 < 2e-16 ***
ORIGIN_SZJWSZ07 -2.3083419 0.0357843 -64.507 < 2e-16 ***
ORIGIN_SZJWSZ08 2.0114225 0.0047956 419.429 < 2e-16 ***
ORIGIN_SZJWSZ09 1.9086705 0.0045255 421.759 < 2e-16 ***
ORIGIN_SZKLSZ01 0.2743166 0.0056908 48.204 < 2e-16 ***
ORIGIN_SZKLSZ02 -0.6443386 0.0074521 -86.463 < 2e-16 ***
ORIGIN_SZKLSZ03 -0.3990113 0.0067213 -59.366 < 2e-16 ***
ORIGIN_SZKLSZ04 -2.1413876 0.0138405 -154.719 < 2e-16 ***
ORIGIN_SZKLSZ05 -1.0913697 0.0121512 -89.816 < 2e-16 ***
ORIGIN_SZKLSZ06 -5.6240764 0.1857405 -30.279 < 2e-16 ***
ORIGIN_SZKLSZ07 -1.1885897 0.0096830 -122.750 < 2e-16 ***
ORIGIN_SZKLSZ08 -1.7018593 0.0114317 -148.872 < 2e-16 ***
ORIGIN_SZLKSZ01 -1.6659670 0.0446420 -37.318 < 2e-16 ***
ORIGIN_SZMDSZ01 -1.1210505 0.0318834 -35.161 < 2e-16 ***
ORIGIN_SZMDSZ02 -0.5096299 0.0116645 -43.691 < 2e-16 ***
ORIGIN_SZMDSZ03 -1.9187039 0.0198291 -96.762 < 2e-16 ***
ORIGIN_SZMPSZ01 -0.5260512 0.0094201 -55.844 < 2e-16 ***
ORIGIN_SZMPSZ02 -0.2905084 0.0077974 -37.257 < 2e-16 ***
ORIGIN_SZMPSZ03 0.3342293 0.0063715 52.457 < 2e-16 ***
ORIGIN_SZMUSZ02 -3.8337096 0.1105053 -34.693 < 2e-16 ***
ORIGIN_SZNTSZ01 -2.9845040 0.0397028 -75.171 < 2e-16 ***
ORIGIN_SZNTSZ02 -3.1812985 0.0249470 -127.522 < 2e-16 ***
ORIGIN_SZNTSZ03 -0.9742991 0.0085424 -114.054 < 2e-16 ***
ORIGIN_SZNTSZ05 -4.2086932 0.0579737 -72.597 < 2e-16 ***
ORIGIN_SZNTSZ06 -4.5831822 0.0583494 -78.547 < 2e-16 ***
ORIGIN_SZNVSZ01 0.3186962 0.0052944 60.195 < 2e-16 ***
ORIGIN_SZNVSZ02 -0.5321136 0.0073747 -72.154 < 2e-16 ***
ORIGIN_SZNVSZ03 -0.9911852 0.0090560 -109.451 < 2e-16 ***
ORIGIN_SZNVSZ04 -0.8329721 0.0099590 -83.640 < 2e-16 ***
ORIGIN_SZNVSZ05 -2.1460777 0.0182401 -117.657 < 2e-16 ***
ORIGIN_SZPGSZ01 -0.5604078 0.0151515 -36.987 < 2e-16 ***
ORIGIN_SZPGSZ02 -0.4025139 0.0085135 -47.279 < 2e-16 ***
ORIGIN_SZPGSZ03 0.6975483 0.0055534 125.608 < 2e-16 ***
ORIGIN_SZPGSZ04 1.2175486 0.0051080 238.363 < 2e-16 ***
ORIGIN_SZPGSZ05 0.3895354 0.0069851 55.767 < 2e-16 ***
ORIGIN_SZPLSZ01 -0.5572701 0.0134473 -41.441 < 2e-16 ***
ORIGIN_SZPLSZ02 -0.9854214 0.0172337 -57.180 < 2e-16 ***
ORIGIN_SZPLSZ03 -1.6991954 0.0472629 -35.952 < 2e-16 ***
ORIGIN_SZPLSZ04 -2.2000217 0.0373580 -58.890 < 2e-16 ***
ORIGIN_SZPLSZ05 -1.7086663 0.0260920 -65.486 < 2e-16 ***
ORIGIN_SZPNSZ01 1.5292867 0.0055102 277.535 < 2e-16 ***
ORIGIN_SZPNSZ02 0.7457519 0.0127815 58.346 < 2e-16 ***
ORIGIN_SZPNSZ03 -1.3659046 0.0216180 -63.184 < 2e-16 ***
ORIGIN_SZPNSZ04 -2.0025379 0.0360655 -55.525 < 2e-16 ***
ORIGIN_SZPNSZ05 -0.9157959 0.0320955 -28.533 < 2e-16 ***
ORIGIN_SZPRSZ01 0.0522611 0.0139142 3.756 0.000173 ***
ORIGIN_SZPRSZ02 1.3063371 0.0053809 242.774 < 2e-16 ***
ORIGIN_SZPRSZ03 0.9963670 0.0054293 183.516 < 2e-16 ***
ORIGIN_SZPRSZ04 -0.0300950 0.0088010 -3.419 0.000627 ***
ORIGIN_SZPRSZ05 1.6840313 0.0050839 331.245 < 2e-16 ***
ORIGIN_SZPRSZ06 -0.8277202 0.0131296 -63.042 < 2e-16 ***
ORIGIN_SZPRSZ07 -2.1698449 0.0177362 -122.340 < 2e-16 ***
ORIGIN_SZPRSZ08 0.4559353 0.0072609 62.793 < 2e-16 ***
ORIGIN_SZQTSZ01 -0.3517047 0.0078770 -44.650 < 2e-16 ***
ORIGIN_SZQTSZ02 -0.8199353 0.0071544 -114.605 < 2e-16 ***
ORIGIN_SZQTSZ03 -0.2457614 0.0065555 -37.490 < 2e-16 ***
ORIGIN_SZQTSZ04 -1.2216614 0.0084050 -145.349 < 2e-16 ***
ORIGIN_SZQTSZ05 -0.7219952 0.0072360 -99.778 < 2e-16 ***
ORIGIN_SZQTSZ06 -0.6729363 0.0076658 -87.784 < 2e-16 ***
ORIGIN_SZQTSZ07 -1.4497690 0.0109365 -132.563 < 2e-16 ***
ORIGIN_SZQTSZ08 -0.2770151 0.0070193 -39.465 < 2e-16 ***
ORIGIN_SZQTSZ09 -0.6157554 0.0078739 -78.202 < 2e-16 ***
ORIGIN_SZQTSZ10 -0.3091547 0.0075471 -40.963 < 2e-16 ***
ORIGIN_SZQTSZ11 -1.9698881 0.0151247 -130.243 < 2e-16 ***
ORIGIN_SZQTSZ12 -2.6449643 0.0205857 -128.485 < 2e-16 ***
ORIGIN_SZQTSZ13 -0.3754107 0.0088433 -42.452 < 2e-16 ***
ORIGIN_SZQTSZ14 -1.6537473 0.0134378 -123.067 < 2e-16 ***
ORIGIN_SZQTSZ15 -0.3435351 0.0131956 -26.034 < 2e-16 ***
ORIGIN_SZRCSZ01 -1.7104390 0.0141179 -121.154 < 2e-16 ***
ORIGIN_SZRCSZ06 -1.1250727 0.0094909 -118.542 < 2e-16 ***
ORIGIN_SZRVSZ01 -3.0220116 0.0339694 -88.963 < 2e-16 ***
ORIGIN_SZRVSZ02 -3.6040075 0.0297641 -121.086 < 2e-16 ***
ORIGIN_SZRVSZ03 -3.2345594 0.0259149 -124.814 < 2e-16 ***
ORIGIN_SZRVSZ04 -3.6900313 0.0575908 -64.073 < 2e-16 ***
ORIGIN_SZRVSZ05 -2.9527570 0.0178582 -165.344 < 2e-16 ***
ORIGIN_SZSBSZ01 0.0238445 0.0078563 3.035 0.002405 **
ORIGIN_SZSBSZ02 -0.5780602 0.0093054 -62.121 < 2e-16 ***
ORIGIN_SZSBSZ03 0.8961719 0.0054586 164.175 < 2e-16 ***
ORIGIN_SZSBSZ04 0.8421798 0.0061888 136.080 < 2e-16 ***
ORIGIN_SZSBSZ05 -0.1682984 0.0078342 -21.482 < 2e-16 ***
ORIGIN_SZSBSZ06 -1.1482701 0.0196421 -58.460 < 2e-16 ***
ORIGIN_SZSBSZ07 -0.8830317 0.0160709 -54.946 < 2e-16 ***
ORIGIN_SZSBSZ08 -1.1039492 0.0174602 -63.226 < 2e-16 ***
ORIGIN_SZSBSZ09 -0.5946691 0.0101961 -58.323 < 2e-16 ***
ORIGIN_SZSESZ02 1.1144933 0.0050948 218.749 < 2e-16 ***
ORIGIN_SZSESZ03 1.1058963 0.0049026 225.574 < 2e-16 ***
ORIGIN_SZSESZ04 0.7427975 0.0056948 130.433 < 2e-16 ***
ORIGIN_SZSESZ05 -0.2812684 0.0069596 -40.414 < 2e-16 ***
ORIGIN_SZSESZ06 0.8168315 0.0055800 146.387 < 2e-16 ***
ORIGIN_SZSESZ07 -2.2842043 0.0231232 -98.784 < 2e-16 ***
ORIGIN_SZSGSZ01 -0.7313790 0.0098957 -73.909 < 2e-16 ***
ORIGIN_SZSGSZ02 -1.1185406 0.0110919 -100.843 < 2e-16 ***
ORIGIN_SZSGSZ03 0.1752618 0.0060508 28.965 < 2e-16 ***
ORIGIN_SZSGSZ04 0.3764395 0.0056165 67.023 < 2e-16 ***
ORIGIN_SZSGSZ05 -1.7203916 0.0118945 -144.637 < 2e-16 ***
ORIGIN_SZSGSZ06 0.4630857 0.0052886 87.563 < 2e-16 ***
ORIGIN_SZSGSZ07 -0.7051233 0.0073133 -96.417 < 2e-16 ***
ORIGIN_SZSKSZ01 0.2053928 0.0100710 20.395 < 2e-16 ***
ORIGIN_SZSKSZ02 1.2630428 0.0063490 198.935 < 2e-16 ***
ORIGIN_SZSKSZ03 -0.3035297 0.0096788 -31.360 < 2e-16 ***
ORIGIN_SZSKSZ04 -1.7952886 0.0359225 -49.977 < 2e-16 ***
ORIGIN_SZSKSZ05 -0.3836861 0.0176686 -21.716 < 2e-16 ***
ORIGIN_SZSLSZ01 -2.5916326 0.0348001 -74.472 < 2e-16 ***
ORIGIN_SZSLSZ04 -0.2251549 0.0088517 -25.436 < 2e-16 ***
ORIGIN_SZSRSZ01 -2.9590365 0.0173638 -170.414 < 2e-16 ***
ORIGIN_SZTHSZ01 -1.9639893 0.0570321 -34.437 < 2e-16 ***
ORIGIN_SZTHSZ03 -1.7281304 0.0272797 -63.349 < 2e-16 ***
ORIGIN_SZTHSZ04 -2.7837906 0.0343179 -81.118 < 2e-16 ***
ORIGIN_SZTHSZ06 -2.1800693 0.0205491 -106.091 < 2e-16 ***
ORIGIN_SZTMSZ01 0.8228136 0.0066824 123.131 < 2e-16 ***
ORIGIN_SZTMSZ02 2.3174781 0.0044978 515.243 < 2e-16 ***
ORIGIN_SZTMSZ03 1.7061757 0.0048615 350.957 < 2e-16 ***
ORIGIN_SZTMSZ04 1.2407899 0.0058389 212.504 < 2e-16 ***
ORIGIN_SZTMSZ05 -0.1000526 0.0124079 -8.064 7.41e-16 ***
ORIGIN_SZTNSZ01 -2.0347519 0.0139596 -145.760 < 2e-16 ***
ORIGIN_SZTNSZ02 -1.8682671 0.0107901 -173.146 < 2e-16 ***
ORIGIN_SZTNSZ03 -2.1737183 0.0146759 -148.115 < 2e-16 ***
ORIGIN_SZTNSZ04 -0.5006452 0.0081501 -61.428 < 2e-16 ***
ORIGIN_SZTPSZ01 -0.6722487 0.0075606 -88.914 < 2e-16 ***
ORIGIN_SZTPSZ02 0.4552916 0.0050191 90.711 < 2e-16 ***
ORIGIN_SZTPSZ03 -0.7865781 0.0072250 -108.869 < 2e-16 ***
ORIGIN_SZTPSZ04 -0.7049044 0.0066456 -106.071 < 2e-16 ***
ORIGIN_SZTPSZ05 -0.5574925 0.0070366 -79.227 < 2e-16 ***
ORIGIN_SZTPSZ06 -0.4247282 0.0068709 -61.815 < 2e-16 ***
ORIGIN_SZTPSZ07 -0.2846984 0.0071030 -40.081 < 2e-16 ***
ORIGIN_SZTPSZ08 -1.0898051 0.0110046 -99.031 < 2e-16 ***
ORIGIN_SZTPSZ09 -0.8092746 0.0079160 -102.232 < 2e-16 ***
ORIGIN_SZTPSZ10 -0.9332072 0.0086809 -107.502 < 2e-16 ***
ORIGIN_SZTPSZ11 -0.0421981 0.0064343 -6.558 5.44e-11 ***
ORIGIN_SZTPSZ12 -0.6330081 0.0078324 -80.819 < 2e-16 ***
ORIGIN_SZTSSZ01 -1.7650409 0.0517357 -34.116 < 2e-16 ***
ORIGIN_SZTSSZ02 1.1707267 0.0094178 124.310 < 2e-16 ***
ORIGIN_SZTSSZ03 0.6581679 0.0095894 68.635 < 2e-16 ***
ORIGIN_SZTSSZ04 0.8736493 0.0104965 83.233 < 2e-16 ***
ORIGIN_SZTSSZ05 0.0957248 0.0178709 5.356 8.49e-08 ***
ORIGIN_SZTSSZ06 1.7581609 0.0206810 85.013 < 2e-16 ***
ORIGIN_SZWCSZ01 0.8097950 0.0105622 76.669 < 2e-16 ***
ORIGIN_SZWCSZ02 -1.9966163 0.0345747 -57.748 < 2e-16 ***
ORIGIN_SZWCSZ03 -5.0687420 0.1474971 -34.365 < 2e-16 ***
ORIGIN_SZWDSZ01 1.4926003 0.0047216 316.124 < 2e-16 ***
ORIGIN_SZWDSZ02 0.9916597 0.0055755 177.859 < 2e-16 ***
ORIGIN_SZWDSZ03 1.5918065 0.0052180 305.062 < 2e-16 ***
ORIGIN_SZWDSZ04 1.3717152 0.0060516 226.669 < 2e-16 ***
ORIGIN_SZWDSZ05 0.6700111 0.0062287 107.569 < 2e-16 ***
ORIGIN_SZWDSZ06 0.8115996 0.0060947 133.165 < 2e-16 ***
ORIGIN_SZWDSZ07 -0.6488914 0.0093567 -69.351 < 2e-16 ***
ORIGIN_SZWDSZ08 -0.3610234 0.0096440 -37.435 < 2e-16 ***
ORIGIN_SZWDSZ09 1.4445461 0.0052279 276.317 < 2e-16 ***
ORIGIN_SZYSSZ01 -0.2039272 0.0069548 -29.322 < 2e-16 ***
ORIGIN_SZYSSZ02 0.8707707 0.0058957 147.697 < 2e-16 ***
ORIGIN_SZYSSZ03 1.8348842 0.0050377 364.231 < 2e-16 ***
ORIGIN_SZYSSZ04 1.0780641 0.0052960 203.564 < 2e-16 ***
ORIGIN_SZYSSZ05 0.3222765 0.0069700 46.237 < 2e-16 ***
ORIGIN_SZYSSZ06 -0.4424689 0.0124866 -35.435 < 2e-16 ***
ORIGIN_SZYSSZ07 -1.0267883 0.0155821 -65.895 < 2e-16 ***
ORIGIN_SZYSSZ08 0.1833117 0.0070935 25.842 < 2e-16 ***
ORIGIN_SZYSSZ09 1.0766070 0.0050451 213.396 < 2e-16 ***
log(DESTIN_AGE25_64) 0.0295428 0.0001051 280.998 < 2e-16 ***
log(dist) -1.7024691 0.0004625 -3681.042 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 36117615 on 14273 degrees of freedom
Residual deviance: 12983718 on 13993 degrees of freedom
AIC: 13068835
Number of Fisher Scoring iterations: 6Spatial Econometric Interactive Modelling (SEIM)
Import necessary packages
devtools:: install_github("LukeCe/spflow", force = TRUE)pacman::p_load(tmap, sf, spdep, sp, Matrix, reshape2, knitr, tidyverse, spflow)Import data
mpsz_nb <- read_rds("data/rds/mpsz_nb.rds")mpsz_flow <- read_rds("data/rds/mpsz_flow.rds")mpsz_var <- read_rds("data/rds/mpsz_var.rds")Create spflow_network-class objects
mpsz_net <- spflow_network( id_net = "sg", node_neighborhood = nb2mat(mpsz_nb$by_contiguity), node_data = mpsz_var, node_key_column = "SZ_CODE")
mpsz_netSpatial network nodes with id: sg
--------------------------------------------------
Number of nodes: 313
Average number of links per node: 6.077
Density of the neighborhood matrix: 1.94% (non-zero connections)
Data on nodes:
SZ_NAME SZ_CODE BUSSTOP_COUNT AGE7_12 AGE13_24 AGE25_64
1 INSTITUTION HILL RVSZ05 2 330 360 2260
2 ROBERTSON QUAY SRSZ01 10 320 350 2200
3 FORT CANNING MUSZ02 6 0 10 30
4 MARINA EAST (MP) MPSZ05 2 0 0 0
5 SENTOSA SISZ01 1 200 260 1440
6 CITY TERMINALS BMSZ17 10 0 0 0
--- --- --- --- --- --- ---
308 NEE SOON YSSZ07 12 90 140 590
309 UPPER THOMSON BSSZ01 47 1590 3660 15980
310 SHANGRI-LA AMSZ05 12 810 1920 9650
311 TOWNSVILLE AMSZ04 9 980 2000 11320
312 MARYMOUNT BSSZ02 25 1610 4060 16860
313 TUAS VIEW EXTENSION TSSZ06 11 0 0 0
SCHOOL_COUNT BUSINESS_COUNT RETAILS_COUNT FINSERV_COUNT ENTERTN_COUNT
1 1 6 26 3 0
2 0 4 207 18 6
3 0 7 17 0 3
4 0 0 0 0 0
5 0 1 84 29 2
6 0 11 14 4 0
--- --- --- --- --- ---
308 0 0 7 0 0
309 3 21 305 30 0
310 3 0 53 9 0
311 1 0 83 11 0
312 3 19 135 8 0
313 0 53 3 1 0
FB_COUNT LR_COUNT COORD_X COORD_Y
1 4 3 103.84 1.29
2 38 11 103.84 1.29
3 4 7 103.85 1.29
4 0 0 103.88 1.29
5 38 20 103.83 1.25
6 15 0 103.85 1.26
--- --- --- --- ---
308 0 0 103.81 1.4
309 5 11 103.83 1.36
310 0 0 103.84 1.37
311 1 1 103.85 1.36
312 3 11 103.84 1.35
313 0 0 103.61 1.26mpsz_net_pairs <- spflow_network_pair( id_orig_net = "sg", id_dest_net = "sg", pair_data = mpsz_flow, orig_key_column = "ORIGIN_SZ", dest_key_column = "DESTIN_SZ")
mpsz_net_pairsSpatial network pair with id: sg_sg
--------------------------------------------------
Origin network id: sg (with 313 nodes)
Destination network id: sg (with 313 nodes)
Number of pairs: 97969
Completeness of pairs: 100.00% (97969/97969)
Data on node-pairs:
DESTIN_SZ ORIGIN_SZ DISTANCE TRIPS
1 RVSZ05 RVSZ05 0 67
314 SRSZ01 RVSZ05 305.74 251
627 MUSZ02 RVSZ05 951.83 0
940 MPSZ05 RVSZ05 5254.07 0
1253 SISZ01 RVSZ05 4975 0
1566 BMSZ17 RVSZ05 3176.16 0
--- --- --- --- ---
96404 YSSZ07 TSSZ06 26972.97 0
96717 BSSZ01 TSSZ06 25582.48 0
97030 AMSZ05 TSSZ06 26714.79 0
97343 AMSZ04 TSSZ06 27572.74 0
97656 BSSZ02 TSSZ06 26681.7 0
97969 TSSZ06 TSSZ06 0 270mpsz_multinet <- spflow_network_multi(mpsz_net, mpsz_net_pairs)base_model <- spflow(
spflow_formula = log(1+TRIPS) ~
O_(BUSSTOP_COUNT +
AGE25_64) +
D_(SCHOOL_COUNT +
BUSINESS_COUNT +
RETAILS_COUNT +
FINSERV_COUNT) +
P_(log(1+DISTANCE)),
spflow_networks = mpsz_multinet
)
base_model--------------------------------------------------
Spatial interaction model estimated by: MLE
Spatial correlation structure: SDM (model_9)
Dependent variable: log(1 + TRIPS)
--------------------------------------------------
Coefficients:
est sd t.stat p.val
rho_d 0.680 0.004 192.554 0.000
rho_o 0.678 0.004 187.732 0.000
rho_w -0.396 0.006 -65.591 0.000
(Intercept) 0.410 0.065 6.266 0.000
(Intra) 1.313 0.081 16.263 0.000
D_SCHOOL_COUNT 0.017 0.002 7.885 0.000
D_SCHOOL_COUNT.lag1 0.002 0.004 0.551 0.581
D_BUSINESS_COUNT 0.000 0.000 3.015 0.003
D_BUSINESS_COUNT.lag1 0.000 0.000 -0.249 0.804
D_RETAILS_COUNT 0.000 0.000 -0.306 0.759
D_RETAILS_COUNT.lag1 0.000 0.000 0.152 0.880
D_FINSERV_COUNT 0.002 0.000 6.787 0.000
D_FINSERV_COUNT.lag1 -0.002 0.001 -3.767 0.000
O_BUSSTOP_COUNT 0.002 0.000 6.806 0.000
O_BUSSTOP_COUNT.lag1 -0.001 0.000 -2.364 0.018
O_AGE25_64 0.000 0.000 7.336 0.000
O_AGE25_64.lag1 0.000 0.000 -2.797 0.005
P_log(1 + DISTANCE) -0.050 0.007 -6.793 0.000
--------------------------------------------------
R2_corr: 0.6942944
Observations: 97969
Model coherence: ValidatedThe originating trip locations caused by bus stops are significant, signalling that the concentration of bus stops and the population has an influence on starting bus trips! Bus stops and Population could be push factors.
Ending trip locations influenced by financial services locations are significant.